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Chemometrics with R [electronic resource] : Multivariate Data Analysis in the Natural and Life Sciences / by Ron Wehrens

Author
Wehrens, Ron
Published
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2020.
Edition
2nd ed. 2020.
Physical Description
XVI, 308 pages 111 illustrations, 82 illustrations in color : online resource
Additional Creators
SpringerLink (Online service)
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Series
Contents
Introduction. - Data -- Preprocessing -- Principal Component Analysis -- Self-Organizing Maps. - Clustering -- Classification -- Multivariate Regression. - Validation -- Variable Selection -- Chemometric Applications.
Summary
This book offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a comprehensive description of the general data analysis paradigm, from exploratory analysis (principal component analysis, self-organizing maps and clustering) to modeling (classification, regression) and validation (including variable selection). It also includes a special section discussing several more specific topics in the area of chemometrics, such as outlier detection, and biomarker identification. The corresponding R code is provided for all the examples in the book; and scripts, functions and data are available in a separate R package. This second revised edition features not only updates on many of the topics covered, but also several sections of new material (e.g., on handling missing values in PCA, multivariate process monitoring and batch correction). .
Subject(s)
ISBN
9783662620274
Digital File Characteristics
PDF
text file
Part Of
Springer Nature eBook
View MARC record | catkey: 31198061